Farmscape online : participatory design of internet meetings with farmers

This paper presents aspects of a longitudinal study in the design and practice of Internet meetings between farmer their advisors and researchers in rural Australia. It reports on the use of Microsoft NetMeeting (NM) by a group of agricultural researchers from Australia's CSIRO (Commonwealth Scientific and Industrial Research Organisation) for regular meetings, over nine years, with farmers and the commercial advisers. It describes lessons drawn from this experience about the conditions under which telecollaborative tools, such as NM and video conferencing, are likely to be both useful and used.

Seasonal activity and abundance of Orosius orientalis (Hemiptera : Cicadellidae) at agricultural sites in Southeastern Australia

Orosius orientalis is a leafhopper vector of several viruses and phytoplasmas affecting a broad range of agricultural crops. Sweep net, yellow pan trap and yellow sticky trap collection techniques were evaluated. Seasonal distribution of O. orientalis was surveyed over two successive growing seasons around the borders of commercially grown tobacco crops. Orosius orientalis seasonal activity as assessed using pan and sticky traps was characterised by a trimodal peak and relative abundance as assessed using sweep nets differed between field sites with peak activity occurring in spring and summer months. Yellow pan traps consistently trapped a higher number of O. orientalis than yellow sticky traps.

Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

N2O emissions from agricultural lands: a synthesis of simulation approaches

Nitrous oxide (N2O) is primarily produced by the microbially-mediated nitrification and denitrification processes in soils. It is influenced by a suite of climate (i.e. temperature and rainfall) and soil (physical and chemical) variables, interacting soil and plant nitrogen (N) transformations (either competing or supplying substrates) as well as land management practices. It is not surprising that N2O emissions are highly variable both spatially and temporally. Computer simulation models, which can integrate all of these variables, are required for the complex task of providing quantitative determinations of N2O emissions. Numerous simulation models have been developed to predict N2O production. Each model has its own philosophy in constructing simulation components as well as performance strengths. The models range from those that attempt to comprehensively simulate all soil processes to more empirical approaches requiring minimal input data. These N2O simulation models can be classified into three categories: laboratory, field and regional/global levels. Process-based field-scale N2O simulation models, which simulate whole agroecosystems and can be used to develop N2O mitigation measures, are the most widely used. The current challenge is how to scale up the relatively more robust field-scale model to catchment, regional and national scales. This paper reviews the development history, main construction components, strengths, limitations and applications of N2O emissions models, which have been published in the literature. The three scale levels are considered and the current knowledge gaps and challenges in modelling N2O emissions from soils are discussed.

Didiman: Australian agricultural extension officers in the territory of Papua and New Guinea, 1945-1975

Historically, the development philosophy for the two Territories of Papua and New Guinea (known as TPNG, formerly two territories, Papua and New Guinea) was equated with economic development, with a focus on agricultural development. To achieve the modification or complete change in indigenous farming systems the Australian Government’s Department of External Territories adopted and utilised a programme based on agricultural extension. Prior to World War II, under Australian administration, the economic development of these two territories, as in many colonies of the time, was based on the institution of the plantation. Little was initiated in agriculture development for indigenous people. This changed after World War II to a rationale based on the promotion and advancement of primary industry, but also came to include indigenous farmers. To develop agriculture within a colony it was thought that a modification to, or in some cases the complete transformation of, existing farming systems was necessary to improve the material welfare of the population. It was also seen to be a guarantee for the future national interest of the sovereign state after independence was granted. The Didiman and Didimisis became the frontline, field operatives of this theoretical model of development. This thesis examines the Didiman’s field operations, the structural organisation of agricultural administration and the application of policy in the two territories.